P.D. Women's College

Multimodal Large Language Models(MLLMs) have shown promising reasoning capabilities in general domains, yet their performance remains limited in specialized settings such as healthcare, particularly for multilingual and low-resource scenarios. This gap is critical in regions like rural India, where patients often express complex medical queries in native Indic languages and rely on multimodal inputs such as medical images. Existing MLLMs, predominantly trained on English-centric data, struggle to support such use cases, limiting equitable access to AI-driven healthcare assistance. To address this challenge, we construct a large-scale multilingual multimodal medical question–answer dataset named \textbf{ArogyaBodha} from eight heterogeneous sources, covering 31 body systems, six imaging modalities, and 21 clinical domains across English and seven major Indian languages. We further propose \textbf{\textit{ArogyaSutra}}, an actor–critic–based multi-agent framework that combines tool grounding with dual-memory mechanisms to support step-wise, reasoning-aware decision making while explicitly retaining past mistakes to prevent their repeated occurrence. The Actor predicts the answer to the multimodal query from visual and memory states, whereas the Critic evaluates actor outcomes and delivers corrective feedback, enabling iterative refinement of the reasoning process. Experiments show that our dataset and framework improve the multilingual medical reasoning accuracy of an MLLM across all Indic languages, with ablation studies validating the effectiveness of each component. Our work supports UN SDGs~3,~4, and~10 by enabling reliable multilingual medical decision support, reducing healthcare inequities, and strengthening inclusive clinical education for underserved communities.

Springs’ water supply is vital for home, agricultural, and drinking purposes in the Aizawl district. The current study assessed specific characteristics of 87 springs that were geotagged and mapped as present in the study area, based on their significance. This research aims to comprehensively investigate and analyze a total of 14 selected physico-chemical parameters of spring water to assess its quality and sustainability for different uses. The evaluated traits encompassed spring water quality, seasonal variations, its sustainability for drinking, and domestic usage. The novelty of this study lies in its comprehensive and technologically advanced approach to assessing spring water resources, with a focus on a relatively under-resourced region, and its integration of hydrological and environmental data to provide holistic and actionable insights. This study used Durov and Piper diagrams for water quality assessment and analysis, which indicates that the springs are mainly alkaline types due to the high concentrations of bicarbonate and carbonate. The basic hydro-chemical characteristics of the study area were found to be of the HCO₃⁻+CO₃²⁻ and Cl⁻+F⁻ types. The PCA result indicated the extracted components 6 and 5 accounted for 68.735

Since the emergence of SARS-CoV-2, the interplay of human behavior, environmental factors, viral evolution, and public health interventions has resulted in unexpected changes in the timing, intensity, and geography of respiratory virus outbreaks. For example, respiratory syncytial viruses (RSV) exhibited a surge during atypical summer months in several countries. Influenza, on the other hand, nearly vanished in the early years of the pandemic, but returned with unusual strength and altered seasonal patterns. Concurrently, new variants of concern in coronaviruses have demonstrated increased airborne transmissibility, greater resilience to environmental conditions, and the ability to evade both natural and vaccine-induced immunity. In this review article, we have synthesized the current understanding of the aerobiology of respiratory infectious viruses, with a particular emphasis on the paradoxical trends observed in recent years. We examined various aspects, including viral morphology and environmental survivability, shifts in seasonality, the drivers of mutation and resistance, and the impact of environmental and climatic factors. Key issues we explored include viral morphology adaptation in response to airborne selective pressures and climate variability influence on the ecology of airborne viruses. Lastly, we investigated future risks and proposed an interdisciplinary framework for monitoring and mitigating airborne viral threats in an ever-changing world.

The skull area of a head MRI possesses incomprehensible information that has aught significance in diagnosis of disease. Conversely, it can effectively degrade the performance of a computer-aided diagnostic (CAD) system and mislead the system into a false diagnosis. Therefore, it is coveted to isolate the skull from the input image before proceeding with the actual diagnosis process. For this purpose, the article proposes a simple algorithm based on digital image processing. The proposed method includes adaptive intensity slicing, adaptive morphology, and innovative ‘Effective Connected-Component Analysis’ operations. The fundamental concept of the proposed method is to separate the skull from the brain using adaptive morphology and then extract the brain component using ‘Effective Connected-Component Analysis’. The comparative analysis shows that the proposed method gives better Sensitivity and Specificity values (93.6 and 96.8) than the other image processing-based state-of-art methods. Moreover, the proposed method is very time efficient and does not require multiple image slices or training data sets.

This study investigates the impact of women's participation in rural tourism on cultural preservation and commercialisation in the rural Himalayas of West Bengal. Using a survey methodology to gauge perceptions, the research examines how women's involvement enhances cultural tourism activities, such as ethnic homestay tourism, preservation of ethnic crafts and festivals, sales of local food and beverages, and the preservation of heritage sites and rural life. The results also highlight the influence of economic status on community engagement, demonstrating that higher-income groups are more involved in cultural preservation efforts. These outcomes underscore the transformative potential of empowering women through rural tourism, aligning with global objectives to promote gender equality and sustainable development. The study recommends that policymakers and stakeholders prioritise empowering women through targeted training, financial support, and inclusive tourism policies to enhance cultural preservation and economic growth in rural communities.